get_intraday_changes

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must compensate but only states it returns a Markdown table. It does not disclose that this is a safe read operation, any rate limits, data freshness, or potential errors. Missing key behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is short, well-structured with Args and Returns sections, and includes an example. Every sentence adds value with no redundancy. Front-loads the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema, the description adequately covers purpose, parameter format, and return format. However, it lacks context on what constitutes an 'abnormal fluctuation' or any edge cases, but these are minor omissions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema coverage, the description adds necessary meaning for the stock_code parameter by specifying the required format (e.g., 300750.SZ) and providing an example. This significantly clarifies usage beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool retrieves intraday chart order book anomaly data, including important trading events and abnormal fluctuations. This is a specific verb+resource combination that distinguishes it from sibling tools like get_kline or get_real_time_data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. The description lacks context about appropriate scenarios, prerequisites, or when to choose this over similar tools like get_market_performance or get_kline.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.